mastR

Bioc current

Markers Automated Screening Tool in R

v1.12.0 · software · MIT + file LICENSE

View on Bioconductor ↗ Source ↗

Release Lineage

Entered 3.17 · Apr 26, 2023

Current · Requires R 4.6

1.0 In 7 of 49 releases 3.23

Description

mastR is an R package designed for automated screening of signatures of interest for specific research questions. The package is developed for generating refined lists of signature genes from multiple group comparisons based on the results from edgeR and limma differential expression (DE) analysis workflow. It also takes into account the background noise of tissue-specificity, which is often ignored by other marker generation tools. This package is particularly useful for the identification of group markers in various biological and medical applications, including cancer research and developmental biology.

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

41 13 exported

Complexity

2.8 avg / 8 max

Call network

41 nodes / 14 edges

Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.

Call graph

Open call graph →

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Lowest coverage

Per-function coverage is not measured for this package yet.

Code

Structure

Lines of code

11,049

Files

109

Compiled share

Has compiled src

Language breakdown

R 5,915 (53.5%)Tests 993 (9%)Docs 2,715 (24.6%)Vignettes 1,426 (12.9%)

API

Exported functions

Internal functions

Testing & CI

Has tests

Yes

Test-to-code ratio

0.17

testthat edition

CI present

Yes

CI type

["github-actions"]

PR gated

Yes

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

–

Unsafe pattern score

Dep constraint coverage

Secret pattern count

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.3.0

System requirements

–

C++ standard

–

License

MIT + file LICENSE

License flags

SPDX valid, OSI approved

History

Versions

First release

2023-04-25

Latest release

2026-04-28

Avg cadence

175 days

Cold removal rate

–

Dep drift

LOC over versions

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.

Documentation

READMEYes · 204 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 67% structuredCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 100%
Return-value docs: 100%
References docs: 0%

Topics

Software

Software › AssayDomain › GeneExpression

Software › ResearchField › Transcriptomics

Software › BiologicalQuestion › DifferentialExpression

Software › WorkflowStep › Visualization

People

Jinjin Chen author maintainer
Ahmed Mohamed author contributor
Chin Wee Tan contributor

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